Welcome to the Cloud Commercial Communities monthly webinar and podcast update. Each month the team focuses on core programs, updates, trends, and technologies that Microsoft partners and customers need to know to increase success using Azure and Dynamics. Make sure you catch a live webinar and participate in live Q&A. If you miss a session, you can review it on demand. Also consider subscribing to the industry podcasts to keep up to date with industry news.
Happening in December Webinars
December 4, 2018 at 11:00 AM Pacific Time
Explore AI industry trends and how the Microsoft AI platform can empower your business processes with Azure AI Services including bots, cognitive services, and Azure machine learning.
December 11, 2018 at 11:00 AM Pacific Time
Learn the publisher onboarding process, best practices around common blockers, plus support resources available.
December 17, 2018 at 1:00 PM Pacific Time
Overview of Azure Container Registry, Azure Container Instances (ACI), Azure Kubernetes Services (AKS), and release automation tools with live demos.
AI is fueling the next wave of transformative innovations that will change the world. With Azure AI, we empower organizations to easily:
Use machine learning to build predictive models that optimize business processes Utilize advanced vision, speech, and language capabilities to build applications that deliver personalized and engaging experiences Apply knowledge mining to uncover latent insights from vast repositories of files
Building on our announcements at Microsoft Ignite in September, I’m excited to share several new announcements we are making at Microsoft Connect(); to enable organizations to easily apply AI to transform their businesses.
Azure Machine Learning service general availability
Today, we are happy to announce the general availability of Azure Machine Learning service. With Azure Machine Learning service, you can quickly and easily build, train, and deploy machine learning models anywhere from the intelligent cloud to the intelligent edge. With features like automated machine learning, organizations can accelerate their model development by identifying suitable algorithms and machine learning pipelines faster. This helps organizations significantly reduce development time, from days to hours. With hyper-parameter tuning, organizations can tune parameters to enhance model accuracy.
Once the model is developed, organizations can easily deploy and manage their models in the cloud and
In countries around the world, natural disasters have been much in the news. If you had a hunch such calamities were increasing, you’re right. In 2017, hurricanes, earthquakes, and wildfires cost $306 billion worldwide, nearly double 2016’s losses of $188 billion.
Natural disasters caused by climate change, extreme weather, and aging and poorly designed infrastructure, among other risks, represent a significant risk to human life and communities. Globally, $94 trillion in new investment is needed to keep pace with population growth, with a large portion of that going toward repair of the built environment. These projects have long cycles due to government authorization processes, huge financial investments, and multi-year building efforts. We need to think creatively about how to accelerate these processes now.
National, state, and local governments and organizations are also grappling with how to update disaster management practices to keep up. The Internet of Things (IoT), artificial intelligence (AI), and machine learning can help. These technologies can improve readiness and lessen the human and infrastructure costs of major events when they do occur. Disaster modeling is an important start and can help shape comprehensive programs to reduce disasters and respond to them effectively.
Anticipating disasters with better data
Join us as we discuss the leading edge of emerging technology in government at the next Microsoft Azure Government DC meetup, Adopting Emerging Tech in Government, on Wednesday, November 28, 2018 from 6:00 to 8:30 PM Eastern Time at 1776 in Washington, DC. If you’re not in the DC-metro area, we invite you to join us via livestream starting at 6:35 PM Eastern Time at aka.ms/azuregovmeetuplive.
You’ll hear how agencies are approaching strategy, challenges, use cases, and workforce readiness as they leverage emerging tech to innovate for their mission including blockchain, artificial intelligence, machine learning, and augmented reality.
RSVP and join us to gain insight from innovators across government agencies who are exploring ways to apply emerging tech to empower their workforce and deliver innovative services to the public.
Featured speakers include:
COL David Robinson, Military Deputy (Acting), Defense Innovation Unit Experimental Ju-Lie McReynolds, Program Manager, US Digital Service, Health & Human Services Meagan Metzger, CEO, Dcode Sujit Mohanty, DoD CTO, Microsoft Federal Jeff Butte, Senior Program Manager, Microsoft Azure Global Government Karina Homme, Senior Director, Microsoft Azure Government About the Microsoft Azure Government user community
The Azure Government DC user community was created as a place to bring
Last week we announced a preview of Docker support for Microsoft Azure Cognitive Services with an initial set of containers ranging from Computer Vision and Face, to Text Analytics. Here we will focus on trying things out, firing up a cognitive service container, and seeing what it can do. For more details on which containers are available and what they offer, read the blog post “Getting started with these Azure Cognitive Service Containers.”
You can run docker in many contexts, and for production environments you will definitely want to look at Azure Kubernetes Service (AKS) or Azure Service Fabric. In subsequent blogs we will dive into doing this in detail, but for now all we want to do is fire up a container on a local dev-box which works great for dev/test scenarios.
You can run Docker desktop on most dev-boxes, just download and follow the instructions. Once installed, make sure that Docker is configured to have at least 4G of RAM (one CPU is sufficient). In Docker for Windows it should look something like this:
Getting the images
The Text Analytics images are available directly from Docker Hub as follows:
Key phrase extraction extracts key talking
As IoT and artificial intelligence become more advanced, smart buildings are also being utilized to drive down energy usage and maintenance costs. They’re providing safer, more comfortable environments while preventing equipment breakdowns and disruptions to occupants. They’re even increasing productivity by adapting to how people live and work.
There’s a growing demand for smart buildings which offer multiple benefits for building owners, managers, and tenants. Some of the trends, scenarios, and payoffs just might surprise you. Attend our upcoming IoT in Action Smart Building webinar to learn more.
Benefits beyond infrastructure and operations
What most people think of when it comes to smart buildings and IoT are the basics around security and infrastructure. This includes egress, surveillance, elevators, parking, as well as building operations like power, HVAC, and water. These are key focus areas that are driving down costs and increasing sustainability, while keeping people safer and more comfortable.
Smart spaces are going beyond meeting these needs. A second less obvious area where IoT is driving change is productivity i.e., how a space can help people get more done in less time. As IoT gets more intelligent, smart spaces can sense the people in them and how they work,
https://azure.microsoft.com/blog/getting-started-with-azure-cognitive-services-in-containers/Building solutions with machine learning often requires a data scientist. Azure Cognitive Services enable organizations to take advantage of AI with developers, without requiring a data scientist. We do this by taking the machine learning models and the pipelines and READ MORE
Edge computing is one of the greatest trends that is not only transforming the cloud market, but creating new opportunities for business and society. At its core, edge computing is about harnessing compute on a device, closest to where insights need to be realized – on a connected car, a piece of machinery, or a remote oil field, for example – so these insights come without delay and with a high-degree of accuracy. This is known as the “intelligent edge” because these devices are constantly learning, often aided by AI and Machine Learning algorithms powered by the intelligent cloud. At Microsoft we see amazing new applications of the intelligent edge and intelligent cloud every day – and yet this opportunity is so expansive – the surface has barely been scratched.
To further advance inquiry and discovery at the edge, today we are announcing Microsoft is donating cloud hardware and services to Carnegie Mellon University’s Living Edge Laboratory. Carnegie Mellon University is recognized as one of the leading global research institutions. Earlier this year, the university announced a $27.5 million semiconductor research initiative to connect edge devices to the cloud. Today’s announcement builds on existing commitments to discovery in the field
This post is co-authored by Anil Kumble, Founder, Spektacom Technologies.
While Cricket is an old sport with a dedicated following of fans across the globe, the game has been revolutionized in the 21st century with the advent of Twenty20 format resulting in a massive growth of interest in the game and fan following worldwide. This has led to an increase in competition as well as a desire among professionals and amateurs likewise, to improve the quality of their game.
As the popularity of the game increased, innovative methods of improving batting techniques evolved. This has also resulted in a need for data-driven assistance for players to assess their quality of game. Spektacom was born with the idea of using non-intrusive sensor technology on cricket bat to harness and power the convergence of data from sticker of “power bats” with insights driven from cloud-powered data analytics, machine learning, and artificial intelligence. Learn more on AI Lab.
Before we highlight how Spektacom built the solution using Microsoft AI, here are some important questions we must answer first.
What is the key area of differentiation that technology can create for sport as an industry?
During the last several years, the industry has
Keeping up with the pace of change in Microsoft Azure can be challenging. Every week there are more than 50 pull requests against the Azure Representational State Transfer (REST) API. Over the past 6 months, we’ve been building the AI-powered extension, Azure Aladdin, to help make using Azure easier. The first interface was a Microsoft docs extension that provided users content recommendations.
Today we are excited to offer the next interface to the Aladdin knowledge base, an experimental Azure Command-line interface (CLI) extension that provides insight and examples based on how other user have seen success using Microsoft Azure.
Install the Azure CLI “Find” extension
We’ve made it straightforward to install experimental extensions in Azure CLI. If you want to install the new “Find” extension, run the following command:
For users of the Azure Cloud Shell, any extension installed will persist between sessions. Below we’re going to examine some of the capabilities of this new extension.
Explains CLI commands
For some features and previews, such as Azure Web App for Containers, there may only be auto-generated reference content without examples.
Shows common commands in a group
The extension can also break down complex groups, such as Azure Monitor